DeepSeek V3.1 vs Mistral Large 2
DeepSeek V3.1 (2026) and Mistral Large 2 (2025) are compact production models from DeepSeek and MistralAI. DeepSeek V3.1 ships a 64K-token context window, while Mistral Large 2 ships a 128K-token context window. On MMLU PRO, DeepSeek V3.1 leads by 13.6 pts. On pricing, Mistral Large 2 costs $0.48/1M input tokens versus $0.56/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Pick DeepSeek V3.1 for general evaluation; Mistral Large 2 is better when long-context analysis matters more.
Specs
| Released | 2026-03-01 | 2025-11-25 |
| Context window | 64K | 128K |
| Parameters | — | 123B |
| Architecture | mixture of experts | decoder only |
| License | Open Source | True |
| Knowledge cutoff | - | 2025-07 |
Pricing and availability
| DeepSeek V3.1 | Mistral Large 2 | |
|---|---|---|
| Input price | $0.56/1M tokens | $0.48/1M tokens |
| Output price | $1.68/1M tokens | $2.4/1M tokens |
| Providers |
Capabilities
| DeepSeek V3.1 | Mistral Large 2 | |
|---|---|---|
| Vision | ||
| Multimodal | ||
| Reasoning | ||
| Function calling | ||
| Tool use | ||
| Structured outputs | ||
| Code execution |
Benchmarks
| Benchmark | DeepSeek V3.1 | Mistral Large 2 |
|---|---|---|
| MMLU PRO | 83.3 | 69.7 |
Deep dive
On shared benchmark coverage, MMLU PRO has DeepSeek V3.1 at 83.3 and Mistral Large 2 at 69.7, with DeepSeek V3.1 ahead by 13.6 points. The largest visible gap is 13.6 points on MMLU PRO, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: Mistral Large 2, tool use: Mistral Large 2, and code execution: DeepSeek V3.1. Both models share vision, multimodal input, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, DeepSeek V3.1 lists $0.56/1M input and $1.68/1M output tokens, while Mistral Large 2 lists $0.48/1M input and $2.4/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts DeepSeek V3.1 lower by about $0.16 per million blended tokens. Availability is 6 providers versus 4, so concentration risk also matters.
Choose DeepSeek V3.1 when coding workflow support and broader provider choice are central to the workload. Choose Mistral Large 2 when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek V3.1 or Mistral Large 2?
Mistral Large 2 supports 128K tokens, while DeepSeek V3.1 supports 64K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, DeepSeek V3.1 or Mistral Large 2?
Mistral Large 2 is cheaper on tracked token pricing. DeepSeek V3.1 costs $0.56/1M input and $1.68/1M output tokens. Mistral Large 2 costs $0.48/1M input and $2.4/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.1 or Mistral Large 2 open source?
DeepSeek V3.1 is listed under Open Source. Mistral Large 2 is listed under True. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, DeepSeek V3.1 or Mistral Large 2?
Both DeepSeek V3.1 and Mistral Large 2 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is better for multimodal input, DeepSeek V3.1 or Mistral Large 2?
Both DeepSeek V3.1 and Mistral Large 2 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run DeepSeek V3.1 and Mistral Large 2?
DeepSeek V3.1 is available on Microsoft Foundry, Fireworks AI, NVIDIA NIM, Together AI, and AWS Bedrock. Mistral Large 2 is available on OpenRouter, IBM watsonx, AWS Bedrock, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
Continue comparing
Last reviewed: 2026-04-24. Data sourced from public model cards and provider documentation.